Identification of a Novel c.3080delC JAG1 Gene Mutation Associated With Alagille Syndrome: Whole Exome Sequencing
Bibliographic record
Abstract
Background Alagille syndrome is an autosomal dominant disorder associated with variable clinical phenotypic features including cholestasis, congenital heart defects, vertebral defects, and dysmorphic facies. Objective Whole exome sequencing (WES) has become technically feasible due to the recent advances in next-generation sequencing technologies, therefore offering new possibilities for mutations or genes identification. Methods WES was used to identify pathogenic variants, which may have significant prognostic implications for patients’ clinical presentation of the proband. In this paper, we have uncovered a novel JAGGED1 gene (JAG1) mutation associated with Alagille syndrome in a 5-year-old girl presented with conjugated hyperbilirubinemia and infantile cholestasis. Results The exome sequencing analysis revealed the presence of a novel JAG1 heterozygous c.3080delC variant in exon 25. The detected variant introduced a stop codon (p.P1027RfsTer9) in the gene sequence, encoding a truncated protein. Our exome observations were confirmed through Sanger sequencing as well. Conclusions Here, we report a case of a patient diagnosed with Alagille syndrome, conjugated hyperbilirubinemia, and infantile cholestasis, with emphasis on its association with the detection of the novel JAG1 mutation, thereby establishing the genetic diagnosis of the disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".